000			01976 a2200253 4500
005			20251013194455.0
008			241205b |||||||| |||| 00| 0 eng d
020			_a9783031204722
041			_aeng
082			_a681.3 _bYaoN
100			_aYao, Kan
245			_aNanophotonics and Machine Learning : _bConcepts, Fundamentals, and Applications / _cKan Yao  and Yuebing Zheng
260			_aSwitzerland: _bSpringer; _c©2023
300			_aix, 178p.
440			_aSpringer Series in Optical Sciences _vv.241
520			_aThis book, the first of its kind, bridges the gap between the increasingly interlinked fields of nanophotonics and artificial intelligence (AI). While artificial intelligence techniques, machine learning in particular, have revolutionized many different areas of scientific research, nanophotonics holds a special position as it simultaneously benefits from AI-assisted device design whilst providing novel computing platforms for AI. This book is aimed at both researchers in nanophotonics who want to utilize AI techniques and researchers in the computing community in search of new photonics-based hardware. The book guides the reader through the general concepts and specific topics of relevance from both nanophotonics and AI, including optical antennas, metamaterials, metasurfaces, and other photonic devices on the one hand, and different machine learning paradigms and deep learning algorithms on the other. It goes on to comprehensively survey inverse techniques for device design, AI-enabled applications in nanophotonics, and nanophotonic platforms for AI. This book will be essential reading for graduate students, academic researchers, and industry professionals from either side of this fast-developing, interdisciplinary field.
650			_aOptics & Photonics
650			_aMicrowaves
650			_aMachine Learning
650			_aOptical Engineering
650			_aMaterials Science
700			_aZheng, Yuebing
942			_cBK
999			_c7050 _d7050